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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Integrated terrain models covering 16,357 square kilometers of the Massachusetts coastal zone and offshore waters were built to provide a continuous elevation and bathymetry terrain model for ocean planning purposes. The area is divided into the following four geographical areas to reduce file size and facilitate publishing: Massachusetts Bay from the Massachusetts-New Hampshire border south to Provincetown and Scituate and east to Stellwagen Bank; Cape Cod Bay from Provincetown to Scituate and south to Hyannis; Buzzards Bay from the Cape Cod Canal southwest to the State border including the Elizabeth Islands and extending north to Fall River and Mount Hope Bay; and Nantucket and Vineyard Sounds, from Hyannis south...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Integrated terrain models covering 16,357 square kilometers of the Massachusetts coastal zone and offshore waters were built to provide a continuous elevation and bathymetry terrain model for ocean planning purposes. The area is divided into the following four geographical areas to reduce file size and facilitate publishing: Massachusetts Bay from the Massachusetts-New Hampshire border south to Provincetown and Scituate and east to Stellwagen Bank; Cape Cod Bay from Provincetown to Scituate and south to Hyannis; Buzzards Bay from the Cape Cod Canal southwest to the State border including the Elizabeth Islands and extending north to Fall River and Mount Hope Bay; and Nantucket and Vineyard Sounds, from Hyannis south...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMHRP, Cape Ann, All tags...


    map background search result map search result map Massachusetts Bay and adjacent land: continuous bathymetry and topography terrain model of the Massachusetts coastal zone and continental shelf, (32-bit GeoTIFF, UTM 19 NAD 83, NAVD 88 vertical datum). Massachusetts Bay and adjacent land: Polygon boundaries for source data of a continuous bathymetry and topography terrain model of the Massachusetts coastal zone and continental shelf: (Esri polygon shapefile, Geographic, NAD 83) USGS 1:125000-scale Quadrangle for Cape Ann, MA 1943 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parker River, MA, 2014 Development: Development delineation: Parker River, MA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Parker River, MA, 2014 DisOcean: Distance to the ocean: Parker River, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parker River, MA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parker River, MA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Parker River, MA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parker River, MA, 2014 Development: Development delineation: Parker River, MA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parker River, MA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parker River, MA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Parker River, MA, 2014 DisOcean: Distance to the ocean: Parker River, MA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parker River, MA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Parker River, MA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parker River, MA, 2014 USGS 1:125000-scale Quadrangle for Cape Ann, MA 1943 Massachusetts Bay and adjacent land: continuous bathymetry and topography terrain model of the Massachusetts coastal zone and continental shelf, (32-bit GeoTIFF, UTM 19 NAD 83, NAVD 88 vertical datum). Massachusetts Bay and adjacent land: Polygon boundaries for source data of a continuous bathymetry and topography terrain model of the Massachusetts coastal zone and continental shelf: (Esri polygon shapefile, Geographic, NAD 83)